Dynamic precision oncology: from static mutation matching to adaptive tumor-host ecosystems

Precision oncology has transformed cancer care by enabling biomarker-guided therapeutic strategies; however, durable clinical benefit remains limited across many tumor types. Emerging evidence suggests that treatment failure cannot be fully explained by static genomic alterations alone, but rather reflects dynamic interactions among tumor evolution, host biology, and therapeutic and healthcare system pressures.

This narrative review examines the biological, technological, clinical, and systemic barriers limiting the effectiveness of precision oncology. We summarize literature identified from PubMed, MEDLINE, and Web of Science (2015-2026), focusing on therapeutic resistance, tumor microenvironment dynamics, longitudinal molecular monitoring, predictive biomarkers, multi-omics integration, adaptive trial design, implementation science, and healthcare disparities. We also discuss emerging concepts in evolutionary oncology, non-genetic resistance mechanisms, phenotypic plasticity, and host genomic variability that influence treatment response and disease progression.

Precision oncology is undergoing a paradigm shift from static mutation-based treatment selection toward adaptive, longitudinal, and systems-oriented cancer management. The key limitation is no longer identification of actionable alterations alone, but the inability to integrate tumor evolution, host factors, and real-time biomarker dynamics into clinical decision-making. Future progress will depend on longitudinal molecular monitoring, adaptive therapeutic sequencing, integrated tumor-host frameworks, and equitable learning healthcare systems.